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Background: Since COVID-19 was declared a pandemic by the World Health Organization on March 11, 2020, the disease has had an unprecedented impact worldwide. Social media such as Reddit can serve as a resource for enhancing situational awareness, particularly regarding monitoring public attitudes and behavior during the crisis. Insights gained can then be utilized to better understand public attitudes and behaviors during the COVID-19 crisis, and to support communication and health-promotion messaging. Objective: The aim of this study was to compare public attitudes toward the 2020-2021 COVID-19 pandemic across four predominantly English-speaking countries (the United States, the United Kingdom, Canada, and Australia) using data derived from the social media platform Reddit. Methods: We utilized a topic modeling natural language processing method (more specifically latent Dirichlet allocation). Topic modeling is a popular unsupervised learning technique that can be used to automatically infer topics (ie, semantically related categories) from a large corpus of text. We derived our data from six country-specific, COVID-19-related subreddits (r/CoronavirusAustralia, r/CoronavirusDownunder, r/CoronavirusCanada, r/CanadaCoronavirus, r/CoronavirusUK, and r/coronavirusus). We used topic modeling methods to investigate and compare topics of concern for each country. Results: Our consolidated Reddit data set consisted of 84,229 initiating posts and 1,094,853 associated comments collected between February and November 2020 for the United States, the United Kingdom, Canada, and Australia. The volume of posting in COVID-19-related subreddits declined consistently across all four countries during the study period (February 2020 to November 2020). During lockdown events, the volume of posts peaked. The UK and Australian subreddits contained much more evidence-based policy discussion than the US or Canadian subreddits. Conclusions: This study provides evidence to support the contention that there are key differences between salient topics discussed across the four countries on the Reddit platform. Further, our approach indicates that Reddit data have the potential to provide insights not readily apparent in survey-based approaches.
ABSTRACT
Background Since COVID-19 was declared a pandemic by the World Health Organization on March 11, 2020, the disease has had an unprecedented impact worldwide. Social media such as Reddit can serve as a resource for enhancing situational awareness, particularly regarding monitoring public attitudes and behavior during the crisis. Insights gained can then be utilized to better understand public attitudes and behaviors during the COVID-19 crisis, and to support communication and health-promotion messaging. Objective The aim of this study was to compare public attitudes toward the 2020-2021 COVID-19 pandemic across four predominantly English-speaking countries (the United States, the United Kingdom, Canada, and Australia) using data derived from the social media platform Reddit. Methods We utilized a topic modeling natural language processing method (more specifically latent Dirichlet allocation). Topic modeling is a popular unsupervised learning technique that can be used to automatically infer topics (ie, semantically related categories) from a large corpus of text. We derived our data from six country-specific, COVID-19–related subreddits (r/CoronavirusAustralia, r/CoronavirusDownunder, r/CoronavirusCanada, r/CanadaCoronavirus, r/CoronavirusUK, and r/coronavirusus). We used topic modeling methods to investigate and compare topics of concern for each country. Results Our consolidated Reddit data set consisted of 84,229 initiating posts and 1,094,853 associated comments collected between February and November 2020 for the United States, the United Kingdom, Canada, and Australia. The volume of posting in COVID-19–related subreddits declined consistently across all four countries during the study period (February 2020 to November 2020). During lockdown events, the volume of posts peaked. The UK and Australian subreddits contained much more evidence-based policy discussion than the US or Canadian subreddits. Conclusions This study provides evidence to support the contention that there are key differences between salient topics discussed across the four countries on the Reddit platform. Further, our approach indicates that Reddit data have the potential to provide insights not readily apparent in survey-based approaches.
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OBJECTIVE: The aim of this study was to address the association between interstitial lung disease and the risk for severity and mortality among patients with coronavirus disease 2019 (COVID-19). METHODS: The electronic databases of PubMed, Web of Science and EMBASE were systematically searched. The pooled effect size with 95 % confidence interval (CI) was computed by a random-effects meta-analysis model. Heterogeneity test, sensitivity analysis, subgroup analysis, meta-regression analysis, Begg's test and Egger's test were performed. RESULTS: A total of sixteen eligible studies with 217,260 COVID-19 patients were enrolled in this meta-analysis. The findings based on adjusted effect estimates indicated that pre-existing interstitial lung disease was significantly associated with higher risk for COVID-19 severity (pooled effect = 1.34 [95 % CI: 1.16-1.55]) and mortality (pooled effect = 1.26 [95 % CI: 1.09-1.46]). Consistent results were observed in the subgroup analysis stratified by sample size, age, the percentage of male patients, study design, setting, the methods for adjustment and the factors for adjustment. The results of meta-regression demonstrated that sample size, age and region might be the potential sources of heterogeneity. Sensitivity analysis exhibited that our results were stable and robust. No publication bias was observed in Egger's test and Begg's test. CONCLUSION: This meta-analysis on the basis of adjusted effect estimates demonstrated that pre-existing interstitial lung disease was independently associated with significantly higher risk for COVID-19 severity and mortality.
Subject(s)
COVID-19 , Lung Diseases, Interstitial , Humans , Male , Publication BiasABSTRACT
OBJECTIVE: This study aimed to evaluate whether there was a significant relationship between anemia and the risk for mortality among coronavirus disease 2019 (COVID-19) patients by a quantitative meta-analysis based on the adjusted effect estimates. METHODS: A systematic search was conducted in electronic databases to identify all published literature. A random-effects meta-analysis model was used to estimate the pooled effect size and 95% confidence interval (CI). Heterogeneity test, Begg's test, subgroup analysis and meta-regression were performed. RESULTS: Twenty-three articles with 573,928 COVID-19 patients were included in the quantitative meta-analysis. There was a significant association between anemia and an elevated risk of COVID-19 mortality (pooled effect size = 1.47, 95% CI [1.30-1.67]). We observed this significant association in the further subgroup analyses by age, proportion of males, sample size, study design, region and setting. Sensitivity analysis exhibited that our results were reliable. Begg's test showed that there was no publication bias. Meta-regression indicated that the tested variables might not be the source of heterogeneity. CONCLUSION: Our meta-analysis based on risk factors-adjusted effect estimates indicated that anemia was independently associated with a significantly elevated risk for mortality among COVID-19 patients.
Subject(s)
Anemia , COVID-19 , Anemia/complications , Anemia/epidemiology , Data Management , Humans , Male , Risk FactorsABSTRACT
Background: Perceptions of tobacco, cannabis, and electronic nicotine delivery systems (ENDS) are continually evolving in the United States. Exploring these characteristics through user generated text sources may provide novel insights into product use behavior that are challenging to identify using survey-based methods. The objective of this study was to compare the topics frequently discussed among Reddit members in cannabis, tobacco, and ENDS-specific subreddits. Methods: We collected 643,070 posts on the social media site Reddit between January 2013 and December 2018. We developed and validated an annotation scheme, achieving a high level of agreement among annotators. We then manually coded a subset of 2,630 posts for their content with relation to experiences and use of the three products of interest, and further developed word cloud representations of the words contained in these posts. Finally, we applied Latent Dirichlet Allocation (LDA) topic modeling to the 643,070 posts to identify emerging themes related to cannabis, tobacco, and ENDS products being discussed on Reddit. Results: Our manual annotation process yielded 2,148 (81.6%) posts that contained a mention(s) of either cannabis, tobacco, or ENDS with 1,537 (71.5%) of these posts mentioning cannabis, 421 (19.5%) mentioning ENDS, and 264 (12.2%) mentioning tobacco. In cannabis-specific subreddits, personal experiences with cannabis, cannabis legislation, health effects of cannabis use, methods and forms of cannabis, and the cultivation of cannabis were commonly discussed topics. The discussion in tobacco-specific subreddits often focused on the discussion of brands and types of combustible tobacco, as well as smoking cessation experiences and advice. In ENDS-specific subreddits, topics often included ENDS accessories and parts, flavors and nicotine solutions, procurement of ENDS, and the use of ENDS for smoking cessation. Conclusion: Our findings highlight the posting and participation patterns of Reddit members in cannabis, tobacco, and ENDS-specific subreddits and provide novel insights into aspects of personal use regarding these products. These findings complement epidemiologic study designs and highlight the potential of using specific subreddits to explore personal experiences with cannabis, ENDS, and tobacco products.